The Molecular Characteristics and Therapeutic Implications of O-Glycan Synthesis in Pancreatic Cancer by Integrating Transcriptome and Single-Cell Data

BACKGROUND: Glycans constitute the primary components of proteins that regulate key carcinogenic processes in cancer progression. This study investigated the significance of O-glycan synthesis in the pathogenesis, outcome, and therapy of pancreatic cancer (PC). METHODS: Transcriptomic data and clinical prognostic information of PC were acquired via TCGA and GEO databases. CSA database was used to obtain single-cell data of PC. The O-glycan biosynthesis signaling pathway and its related genes were acquired via the MSigDB platform. The nonnegative matrix factorization (NMF) clustering was utilized to construct the O-glycan biosynthesis-associated molecular subtypes in PC. The LASSO and Cox regression were utilized to build the prognostic prediction model. We utilized real-time quantitative PCR (qRT-PCR) to verify the expressed levels of model genes. Single-cell analysis was utilized to investigate the levels of target genes and O-glycan biosynthesis signaling pathway in the PC tumour microenvironment. RESULTS: : We obtained 30 genes related to O-glycan biosynthesis, among which 15 were associated with the prognosis of PC. All PC samples were grouped into two distinct molecular subtypes associated with O-glycan biosynthesis: OGRGcluster C1 and OGRGcluster C2, and compared to OGRGcluster C1. PCs in OGRGcluster C2 had a more advanced clinical stage and pathological grade, worse prognosis, and more active O-glycan biosynthesis function. Immune analysis indicated that naïve B cell, CD8+ T cell, memory-activated CD4+ T cell, and monocytes displayed remarkably higher infiltration levels in OGRGcluster C1 while resting NK cell, macrophages M0, resting dendritic cell, activated dendritic cell, and neutrophils exhibited markedly higher infiltration levels in OGRGcluster C2. OGRGcluster C1 exhibited higher sensitivities to drugs, such as cisplatin, irinotecan, KRAS(G12C) inhibitor-12, oxaliplatin, paclitaxel, and sorafenib. Besides, we built the O-glycan biosynthesis-related prognostic model (including SPRR1B, COL17A1, and ECT2) with a good prediction performance. SPRR1B, COL17A1, and ECT2 were remarkably highly expressed in PC tissues and linked to a poor outcome. Single-cell analysis revealed that O-glycan biosynthesis was observed only in PC, and consistent with this, the target genes were significantly enriched in PC. CONCLUSION: We first constructed molecular subtypes and prognostic models related to O-glycan biosynthesis in PC. It is clear that O-glycan biosynthesis is related to the development, prognosis, immune microenvironment, and treatment of PC. This provides new strategies for stratification, diagnosis, and treatment of PC patients.

Fuzheng Nizeng Decoction regulated ferroptosis and endoplasmic reticulum stress in the treatment of gastric precancerous lesions: A mechanistic study based on metabolomics coupled with transcriptomics.

Background: Fuzheng Nizeng Decoction (FZNZ) has a history of decades in gastric precancerous lesions (GPL) treatment, which has shown clear clinical efficacy. Blocking GPL is a key measure to reduce the incidence of gastric cancer (GC). Therefore, we aim to investigate the mechanism of FZNZ-induced ferroptosis and endoplasmic reticulum (ER) in MNNG-induced gastric precancerous lesion (MC) cells, which has been rarely studied in Traditional Chinese Medicine (TCM). Methods: First, CCK8 and lactate dehydrogenase assays were conducted to study the potential effect of FZNZ on MC cells. Second, combined transcriptomic and metabolomic analysis were used to explore the effect and mechanism of FZNZ. Functionally, the occurrence of ferroptosis was assessed by transmission electron microscopy morphological observation and measurement of ferrous iron levels, lipid peroxidation, and glutathione levels. Finally, the expression levels of mRNAs or proteins related to ferroptosis and ER stress were determined by qPCR or western blot assays, respectively. Results: FZNZ inhibited MC cells viability and induced cell death. By metabolomics coupled with transcriptomics analysis, we found that the mechanism of FZNZ treatment induced ferroptosis and was related to glutathione metabolism and ER stress. We then, for the first time, found that FZNZ induced ferroptosis, which contributed to an increase in intracellular ferrous iron, reactive oxygen species, and malondialdehyde and a decrease in glutathione. Meanwhile, the protein level of glutathione peroxidase 4 (GPX4) was decreased. The mRNA levels of ATF3/CHOP/CHAC1, which are related to ferroptosis and ER stress, were also upregulated. Conclusion: Our results elaborate that FZNZ could induce ferroptosis and ER stress in MC cells, and reduce GPX4/GSH. ATF3/CHOP/CHAC1 may play a crosstalk role, which provides a new molecular mechanism for the treatment of GPL.

Identification of hub genes associated with COVID-19 and idiopathic pulmonary fibrosis by integrated bioinformatics analysis.

INTRODUCTION: The coronavirus disease 2019 (COVID-19), emerged in late 2019, was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The risk factors for idiopathic pulmonary fibrosis (IPF) and COVID-19 are reported to be common. This study aimed to determine the potential role of differentially expressed genes (DEGs) common in IPF and COVID-19. MATERIALS AND METHODS: Based on GEO database, we obtained DEGs from one SARS-CoV-2 dataset and five IPF datasets. A series of enrichment analysis were performed to identify the function of upregulated and downregulated DEGs, respectively. Two plugins in Cytoscape, Cytohubba and MCODE, were utilized to identify hub genes after a protein-protein interaction (PPI) network. Finally, candidate drugs were predicted to target the upregulated DEGs. RESULTS: A total of 188 DEGs were found between COVID-19 and IPF, out of which 117 were upregulated and 71 were downregulated. The upregulated DEGs were involved in cytokine function, while downregulated DEGs were associated with extracellular matrix disassembly. Twenty-two hub genes were upregulated in COVID-19 and IPF, for which 155 candidate drugs were predicted (adj.P.value < 0.01). CONCLUSION: Identifying the hub genes aberrantly regulated in both COVID-19 and IPF may enable development of molecules, encoded by those genes, as therapeutic targets for preventing IPF progression and SARS-CoV-2 infections.

Computational recognition of SNOMED CT codes from ED case notes.

This paper is a study of patient notes from an emergency department and a determination of their consistency for correct SNOMED CT encoding of the diagnosis, and comparison with a clinical language processing (CLP) system that determined the SCT diagnoses. Three set of notes were reviewed by a clinician with 500 records in each where: the clinician and CLP codes where the same (Matched Set); where they were different (Unmatched Set); and, where the clinicians had failed to enter a code (Unassigned Set) giving accuracies of 75%, 33.4% and 44.9% respectively.